Systems for touchless detection and recognition of gestures are known. Such systems may be based on capacitive (e.g., surface capacitive, projected capacitive, mutual capacitive, or self capacitive), infrared, optical imaging, dispersive signal, ultrasonic or acoustic pulse recognition sensor technology.
Capacitive sensor systems, for example, can be realized by generating an alternating electrical field and measuring the potential difference (i.e., the voltage) obtained at a sensor electrode within the field. Depending on the implementation, a single electrode may be used, or a transmitting and one or more receiving electrodes may be used. The voltage at the sensor electrode(s) is a measure for the capacitance between the sensor electrode and its electrical environment. That is, it is influenced by objects like a human finger or a hand which may in particular perform a gesture within the detection space provided by the electrode arrangement. Further, from this voltage, for example, the distance of a finger or the gesture may be deduced. This information can be used for human-machine interfaces.
Given a three dimensional positioning system, the straightforward and most high level approach for gesture detection is to take the x/y position estimate as input to the automatic gesture recognition system and use the z-distance for start/stop criteria. As the position estimate is the outcome of one or more stages in which the sensor data is processed (calibration, non linear relation of calibrated sensor value and distance, position being trigonometric function of distances), and each stage introduces extra uncertainty, using x/y/z estimate can be more prone to errors than using data from earlier processing stages.